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--- |
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language: |
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- eu |
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license: apache-2.0 |
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base_model: openai/whisper-base |
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tags: |
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- whisper-event |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_16_1 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Base Basque |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: mozilla-foundation/common_voice_16_1 eu |
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type: mozilla-foundation/common_voice_16_1 |
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config: eu |
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split: test |
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args: eu |
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metrics: |
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- name: Wer |
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type: wer |
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value: 16.17652806002814 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Whisper Base Basque |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the mozilla-foundation/common_voice_16_1 eu dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5038 |
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- Wer: 16.1765 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2.5e-05 |
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- train_batch_size: 128 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 256 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- training_steps: 40000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:| |
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| 0.0225 | 10.0 | 1000 | 0.3059 | 19.0812 | |
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| 0.0037 | 20.0 | 2000 | 0.3530 | 18.4618 | |
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| 0.0012 | 30.0 | 3000 | 0.3724 | 17.9332 | |
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| 0.0004 | 40.0 | 4000 | 0.4025 | 17.8951 | |
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| 0.0002 | 50.0 | 5000 | 0.4245 | 17.8951 | |
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| 0.0001 | 60.0 | 6000 | 0.4459 | 17.9772 | |
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| 0.0001 | 70.0 | 7000 | 0.4665 | 18.0163 | |
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| 0.0 | 80.0 | 8000 | 0.4882 | 18.1081 | |
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| 0.0003 | 90.0 | 9000 | 0.3803 | 16.3807 | |
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| 0.0001 | 100.0 | 10000 | 0.4047 | 16.2293 | |
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| 0.0001 | 110.0 | 11000 | 0.4207 | 16.2420 | |
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| 0.0001 | 120.0 | 12000 | 0.4353 | 16.2879 | |
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| 0.0 | 130.0 | 13000 | 0.4502 | 16.3700 | |
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| 0.0 | 140.0 | 14000 | 0.4653 | 16.5087 | |
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| 0.0 | 150.0 | 15000 | 0.4805 | 16.4393 | |
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| 0.0 | 160.0 | 16000 | 0.4964 | 16.4941 | |
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| 0.0 | 170.0 | 17000 | 0.5128 | 16.5107 | |
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| 0.0 | 180.0 | 18000 | 0.5285 | 16.6377 | |
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| 0.0 | 190.0 | 19000 | 0.5457 | 16.6572 | |
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| 0.0102 | 200.0 | 20000 | 0.4229 | 18.1902 | |
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| 0.0 | 210.0 | 21000 | 0.4498 | 16.2117 | |
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| 0.0 | 220.0 | 22000 | 0.4646 | 16.2146 | |
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| 0.0 | 230.0 | 23000 | 0.4754 | 16.1961 | |
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| 0.0 | 240.0 | 24000 | 0.4853 | 16.1863 | |
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| 0.0 | 250.0 | 25000 | 0.4946 | 16.1912 | |
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| 0.0 | 260.0 | 26000 | 0.5038 | 16.1765 | |
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| 0.0 | 270.0 | 27000 | 0.5133 | 16.2215 | |
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| 0.0 | 280.0 | 28000 | 0.5228 | 16.2224 | |
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| 0.0 | 290.0 | 29000 | 0.5326 | 16.2557 | |
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| 0.0 | 300.0 | 30000 | 0.5427 | 16.2420 | |
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| 0.0 | 310.0 | 31000 | 0.5525 | 16.2635 | |
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| 0.0 | 320.0 | 32000 | 0.5624 | 16.2957 | |
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| 0.0 | 330.0 | 33000 | 0.5706 | 16.3299 | |
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| 0.0 | 340.0 | 34000 | 0.5798 | 16.3534 | |
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| 0.0 | 350.0 | 35000 | 0.5880 | 16.3495 | |
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| 0.0 | 360.0 | 36000 | 0.5948 | 16.3622 | |
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| 0.0 | 370.0 | 37000 | 0.6005 | 16.3934 | |
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| 0.0 | 380.0 | 38000 | 0.6045 | 16.3876 | |
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| 0.0 | 390.0 | 39000 | 0.6074 | 16.4325 | |
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| 0.0 | 400.0 | 40000 | 0.6085 | 16.4315 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
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